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    A participatory GIS approach to flood risk assessment of informal settlements the case of Cape Town

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    Includes abstract.Includes bibliographical references.Rural-urban migrations have contributed to the steady increase in the population of Cape Town. Many of the migrants have settled in informal settlements because they cannot afford to rent or buy decent housing. Many of these settlements are however located on marginal and often poorly drained land. Consequently, most of these settlements are prone to flooding after prolonged rainfall. Current flood risk management techniques implemented by the authorities of the Cape Town City Council (CTCC) are ideal for formally planned settlements but are not designed to support informal settlements...This study sought to investigate a methodology that the CTCC could use to improve flood risk assessment

    λ„μ‹œν™μˆ˜ 저감을 μœ„ν•œ 근거기반 κ³„νš : μ„œμšΈμ‹œλ₯Ό μ€‘μ‹¬μœΌλ‘œ

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    ν•™μœ„λ…Όλ¬Έ (석사) -- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : 농업생λͺ…κ³Όν•™λŒ€ν•™ μƒνƒœμ‘°κ²½Β·μ§€μ—­μ‹œμŠ€ν…œκ³΅ν•™λΆ€(μƒνƒœμ‘°κ²½ν•™), 2021. 2. 강쀀석.졜근 κΈ°ν›„λ³€ν™”λ‘œ 인해 λ°œμƒλ˜κ³  μžˆλŠ” μ‚¬νšŒ/경제적 ν”Όν•΄λŠ” κΈ‰μ†νžˆ μ¦κ°€ν•˜κ³  μžˆλ‹€. κΈ°ν›„λ³€ν™”λ‘œ μΈν•œ 2차적 ν”Όν•΄λ‘œλŠ” 폭염, ν™μˆ˜ 등이 μžˆλ‹€. κ·Έμ€‘μ—μ„œ κ·Ήν•œ κ°•μš°λŠ” 도심지역에 큰 ν”Όν•΄λ₯Ό λ°œμƒμ‹œν‚€κ³  μžˆλ‹€. λŒ€ν‘œμ μœΌλ‘œλŠ” 2011λ…„ λ°œμƒν•œ μ§‘μ€‘ν˜Έμš° 등이 μžˆλŠ”λ°, λ‹Ήμ‹œμ—λŠ” μ΅œλŒ€ 110.5 mm/hr의 기둝적인 κ°•μˆ˜κ°€ λ‚΄λ Έλ‹€. ν˜„λŒ€ λ„μ‹œμ—μ„œ λ°œμƒν•˜λŠ” ν™μˆ˜μ˜ λŒ€λΆ€λΆ„ 원인은 λΆˆνˆ¬μˆ˜μ„± 포μž₯면의 κΈ‰κ²©ν•œ 증가와 λ‚΄μˆ˜λ°°μ œ 뢈λŠ₯, λ¬Όμˆœν™˜ μ‹œμ„€ λΆ€μž¬ λ“±μ˜ 원인이 μžˆλ‹€. κΈ°μƒμ²­μ—μ„œ μ œκ³΅ν•˜λŠ” κΈ°ν›„λ³€ν™” μ‹œλ‚˜λ¦¬μ˜€μ— λ”°λ₯΄λ©΄, ν–₯ν›„ 100λ…„κ°„ λ„μ‹œμ˜ 평균 κ°•μˆ˜λŸ‰μ€ 쀄어듀 κ²ƒμœΌλ‘œ νŒŒμ•…λœλ‹€. ν•˜μ§€λ§Œ, μΌμ‹œμ— ν­μš°κ°€ λ‚΄λ¦¬λŠ” λΉˆλ„κ°€ μ¦κ°€ν•˜κ³  ꡭ지성 ν”Όν•΄κ°€ λšœλ ·ν•˜κ²Œ λ°œμƒν•  κ²ƒμœΌλ‘œ νŒλ‹¨λœλ‹€. ν˜„μž¬ μƒνƒœμ˜ κΈ°λ°˜μ‹œμ„€λ“€μ— λ³΄μˆ˜λ‚˜ λ°©μ–΄κΈ°μˆ μ΄ μˆ˜λ¦½λ˜μ§€ μ•ŠμœΌλ©΄, κ·Έ ν”Όν•΄λŠ” 상당할 κ²ƒμœΌλ‘œ νŒλ‹¨λœλ‹€. 이에 λ³Έ μ—°κ΅¬λŠ” 총 μ„Έ 가지 연ꡬ λͺ©ν‘œλ₯Ό μˆ˜λ¦½ν•˜μ—¬ μˆ˜ν–‰ν•˜μ˜€λ‹€. 첫 번째, κΈ°μƒμ²­μ—μ„œ μ œκ³΅ν•˜λŠ” κΈ°ν›„λ³€ν™” μ‹œλ‚˜λ¦¬μ˜€(RCP 4.5/RCP 8.5)둜 인해 λ°œμƒν•  수 μžˆλŠ” ν–₯ν›„ 80λ…„(2020λ…„-2100λ…„)의 λ„μ‹œ ν™μˆ˜ ν”Όν•΄λŸ‰μ„ μ •λŸ‰μ μœΌλ‘œ λΆ„μ„ν•œλ‹€. 두 번째, μ •λŸ‰μ μœΌλ‘œ λΆ„μ„λœ ν”Όν•΄λŸ‰μ— κΈ°λ°˜ν•œ μž¬ν•΄ 저감 μ‹œμ„€μ„ μ„ μ •ν•˜κ³ , μž¬ν•΄μ˜ μ €κ°λŸ‰μ„ λΆ„μ„ν•œλ‹€. 이λ₯Ό 톡해 κ·Όκ±° 기반(Evidence-Based Planning)의 μ‹œμ„€λ°°μΉ˜ 및 μ„€κ³„ν•œλ‹€. μž¬ν•΄ 저감 μ‹œμ„€μ€ 미래 μ„ΈλŒ€κ°€ μ§€μ†μ μœΌλ‘œ μ‚¬μš©ν•  수 μžˆλŠ” μΉœν™˜κ²½(Eco-Friendly) μ‹œμ„€λ¬Όμ„ μ„ μ •ν•˜μ˜€λ‹€. μ„Έ 번째, HCFD (Hazard Capacity Factor Design) λͺ¨λΈμ˜ κ°œλ°œμ„ 톡해, ν–₯ν›„ λ³€ν™”ν•  수 μžˆλŠ” μ‹œμ„€λ¬Όλ“€μ˜ μš©λŸ‰κ³Ό μ„±λŠ₯에 λŒ€ν•΄ μ •λŸ‰μ μœΌλ‘œ λΆ„μ„ν•œλ‹€. HCFD λͺ¨λΈμ€ 저감 κΈ°μˆ μ„ μœ μ§€ν•˜λŠ” 방법을 κ³ λ €ν•˜λŠ”λ° μ‚¬μš©λœλ‹€. μ΄λŸ¬ν•œ λͺ©ν‘œλ₯Ό λ‹¬μ„±ν•˜κΈ° μœ„ν•΄μ„œ λ°©μ–΄ 기술둜 총 μ„Έ 가지λ₯Ό λ„μž…ν•˜μ˜€λ‹€. μ €λ₯˜μ‘°, νˆ¬μˆ˜μ„± 포μž₯ 그리고 μƒνƒœμˆ˜λ‘œκ°€ 이에 ν•΄λ‹Ήν•œλ‹€. μ €λ₯˜μ‘°μ˜ 경우, ν™˜κ²½λΆ€μ—μ„œ μ§€μ •ν•˜κ³  μžˆλŠ” 법령을 μ°Έκ³ ν•˜μ—¬ λ„μž… κ°€λŠ₯ν•œ μš©λŸ‰μ„ νŒŒμ•…ν•˜μ˜€λ‹€. νˆ¬μˆ˜μ„±ν¬μž₯κ³Ό μƒνƒœμˆ˜λ‘œλŠ” λ²•λ ΉμœΌλ‘œ λͺ…ν™•νžˆ κ·œμ •ν•˜λŠ” 섀계 지침이 없기에, 타 연ꡬ λ³΄κ³ μ„œλ₯Ό μ°Έκ³ ν•˜μ˜€λ‹€. 각 κΈ°μˆ λ“€μ˜ λ„μž… 규λͺ¨λ₯Ό μ‚°μ •ν•˜κΈ° μœ„ν•΄μ„œ Arc-GIS ArcHydro Plug in을 μ‚¬μš©ν•˜μ˜€κ³  Watershedλ₯Ό λΆ„μ„ν•˜μ˜€λ‹€. Watershed에 영ν–₯을 λ―ΈμΉ˜λŠ” λ²”μœ„λ₯Ό νŒŒμ•…ν•˜κΈ° μœ„ν•΄μ„œ κΈ°ν›„λ³€ν™”μ‹œλ‚˜λ¦¬μ˜€μ—μ„œ μ œκ³΅ν•˜λŠ” κ°•μˆ˜λŸ‰μ„ μ‹œκ°„ λ‹¨μœ„λ‘œ λΆ„μ„ν•˜μ˜€κ³ , 이λ₯Ό μœ„ν•΄ Huff Curve 곡식을 μ‚¬μš©ν•˜μ˜€λ‹€. μœ„μ—μ„œ μ–ΈκΈ‰λœ μ„Έ 가지 κΈ°μˆ μ€ λΉ—λ¬Όμ˜ μ €μž₯ μš©λŸ‰μ„ μ¦κ°€μ‹œμΌœ ν™μˆ˜ 완화에 κΈ°μ—¬ν•  κ²ƒμœΌλ‘œ νŒλ‹¨λœλ‹€. μ„Έ 가지 κΈ°μˆ μ„ λͺ¨λ‘ λ„μž…ν•˜μ˜€μ„ λ•Œ 2050λ…„κ³Ό 2060λ…„μ—λŠ” RCP 8.5 μ‹œλ‚˜λ¦¬μ˜€μ˜ λͺ¨λ“  ν™μˆ˜ν”Όν•΄λ₯Ό 저감할 수 μžˆμ„ κ²ƒμœΌλ‘œ νŒλ‹¨λœλ‹€. 2070λ…„ μ΄ν›„μ—λŠ” 유좜이 λ°œμƒν•  κ²ƒμœΌλ‘œ λΆ„μ„λ˜μ§€λ§Œ, 적응 κΈ°μˆ μ„ 톡해 ν™μˆ˜λ₯Ό 크게 쀄일 수 μžˆμ„ κ²ƒμœΌλ‘œ μ˜ˆμΈ‘λœλ‹€. λ³Έ 연ꡬ λ…Όλ¬Έμ—μ„œλŠ” 10λ…„ λ‹¨μœ„μ˜ ν™μˆ˜μ™€ μ μ‘λŸ‰μ„ μ‚°μ •ν•˜μ˜€μ§€λ§Œ, μΆ”ν›„ 후속 μ—°κ΅¬μ—μ„œλŠ” 1λ…„ λ‹¨μœ„μ˜ 뢄석이 μ‹€μ‹œλ˜μ–΄μ•Ό ν•  κ²ƒμœΌλ‘œ νŒλ‹¨λœλ‹€. λ˜ν•œ μ €λ₯˜μ‘° 내뢀에 ν‡΄μ λ˜λŠ” λΉ„μ μ˜€μ—Όμ›μ˜ μ²­μ†Œ μ‹œκΈ°κ°€ μ‚°μ •λ˜μ—ˆμŠ΅λ‹ˆλ‹€. μ €λ₯˜μ‘°μ˜ 경우 MOUSE νšŒκ·€ 뢄석을 톡해 내뢀에 μΆ•μ λœ λΉ„μ μ˜€μ—Όμ› 제거 μ‹œκΈ°λ₯Ό μ‚°μ •ν•˜μ˜€λ‹€. λΉ—λ¬Ό μ €λ₯˜μ‘° λ‚΄λΆ€ κ΄€λ¦¬λŠ” 크게 μ£Όμ˜λ‹¨κ³„, μΌλ°˜λ‹¨κ³„, μ•ˆμ „λ‹¨κ³„λ‘œ μ§€λ°©μžμΉ˜λ‹¨μ²΄λ₯Ό κ΅¬λΆ„ν•˜μ˜€λ‹€. μ£Όμ˜λ‹¨κ³„μ— ν•΄λ‹Ήν•˜λŠ” μ§€λ°©μžμΉ˜λ‹¨μ²΄λŠ” 9개, μΌλ°˜λ‹¨κ³„μ— ν•΄λ‹Ήν•˜λŠ” μ§€λ°©μžμΉ˜λ‹¨μ²΄λŠ” 10개, μ•ˆμ „λ‹¨κ³„μ— ν•΄λ‹Ήν•˜λŠ” μ§€λ°©μžμΉ˜λ‹¨κ³„λŠ” 5κ°œκ°€ ν•΄λ‹Ήν•œλ‹€. 이 μ—°κ΅¬μ˜ κ²°κ³Όλ₯Ό 톡해 λ„μΆœλœ κ²°λ‘  및 μ˜μ˜λŠ” μ„Έ κ°€μ§€λ‘œ μš”μ•½λœλ‹€. 첫째, λ³Έ μ—°κ΅¬λŠ” κΈ°ν›„λ³€ν™” μ‹œλ‚˜λ¦¬μ˜€μ— 따라 λ°œμƒν•  μˆ˜μžˆλŠ” ν™μˆ˜ κ°€λŠ₯성을 10λ…„ 주기둜 λΆ„μ„ν–ˆλ‹€.RCP 8.5 μ‹œλ‚˜λ¦¬μ˜€μ™€ RCP 4.5 μ‹œλ‚˜λ¦¬μ˜€ λͺ¨λ‘ 2070λ…„ 이후에 λΉˆλ²ˆν•œ ν™μˆ˜μ˜ 좔이λ₯Ό λ³Ό 수 μžˆμ—ˆλ‹€. RCP 8.5 μ‹œλ‚˜λ¦¬μ˜€μ˜ 2090년에 κ°•μˆ˜λŸ‰μ΄ κ°€μž₯ λ§Žμ„ κ²ƒμœΌλ‘œ μ˜ˆμƒλœλ‹€. RCP 4.5 μ‹œλ‚˜λ¦¬μ˜€ 2100λ…„μ˜ 경우, μ΅œλŒ€ 690 mm, μ‹œκ°„λ‹Ή κ°•μˆ˜λŸ‰μ€ 238 mmκΉŒμ§€ 내릴 κ²ƒμœΌλ‘œ νŒλ‹¨λœλ‹€. 두 번째, λ³Έ 연ꡬ 논문은 각 기술의 μš©λŸ‰μ„ μžμΉ˜κ΅¬λ³„λ‘œ λΆ„μ„ν•˜μ˜€λ‹€. λ³Έ μ—°κ΅¬μ—μ„œ κ°€μ •ν•œ μ„€μΉ˜ κ·œμ •μ— λ”°λ₯΄λ©΄ μ„œμšΈμ‹œ 전역에 μ„€μΉ˜ν•  수 μžˆλŠ” λΉ—λ¬Ό μ €λ₯˜μ‘°μ˜ λΆ€ν”ΌλŠ” 776,588 mΒ³, νˆ¬μˆ˜μ„± 포μž₯은 89,049 mΒ³, μƒνƒœμˆ˜λ‘œλŠ” 81,986 m³이닀. 각 μ§€λ°©μžμΉ˜λ‹¨μ²΄κ°€ 두 가지 κΈ°μˆ λ§Œμ„ μ μš©ν•˜μ˜€μ„ λ•Œ 효율적인 쑰합을 μ œμ•ˆν•œ 것은 λ³Έ 연ꡬ가 κ°€μ§€λŠ” μ€‘μš”ν•œ μ˜μ˜μž…λ‹ˆλ‹€. μ…‹μ§Έ, 각 μž¬ν•΄μ €κ° 기술둜 저감할 수 μžˆλŠ” μœ μΆœλŸ‰μ„ μ •λŸ‰ν™”ν–ˆμŠ΅λ‹ˆλ‹€. 이 μ—°κ΅¬λŠ” 지역 μ°¨μ›μ˜ 뢄산적 ν˜•νƒœμ˜ ν™μˆ˜κ°€ 더 자주 λ°œμƒν•˜κ³ , μž¬λ‚œ 저감 기술의 μ •λŸ‰μ  효과λ₯Ό λΆ„μ„ν•˜μ˜€λ‹€λŠ”λ° μ˜μ˜κ°€ μžˆλ‹€. λ³Έ μ—°κ΅¬μ˜ ν•œκ³„λŠ” λ„€ λΆ€λΆ„μœΌλ‘œ λ‚˜λˆŒ 수 μžˆλ‹€. 첫 번째 ν•œκ³„λŠ” κΈ°ν›„λ³€ν™” μ‹œλ‚˜λ¦¬μ˜€μ— λŒ€ν•œ λΆˆν™•μ‹€μ„±μ΄λ‹€. νƒ„μ†Œ λ°°μΆœλŸ‰μ΄λ‚˜ μ‹œλ‚˜λ¦¬μ˜€μ˜ λ³€ν™”λŠ” κ°•μˆ˜λŸ‰ 값을 크게 λ³€κ²½ν•  수 있기 λ•Œλ¬Έμ— 였λ₯˜κ°€ 적은 μ‹œλ‚˜λ¦¬μ˜€λ₯Ό μ‚¬μš©ν•˜λ©΄ ν–₯ν›„ 연ꡬ가 더 μ€‘μš”ν•œ μ—°κ΅¬λ‘œ λ°œμ „ν•  κ²ƒμœΌλ‘œ νŒλ‹¨λœλ‹€. 졜근 κΈ°ν›„λ³€ν™” μ‹œλ‚˜λ¦¬μ˜€μ˜ λΆˆν™•μ‹€μ„±μ„ 쀄일 수 μžˆλŠ” 연ꡬ가 ν™œλ°œνžˆ 진행 쀑이기 λ•Œλ¬Έμ—, 첫 번째 ν•œκ³„μ μ„ λ³΄μ™„ν•œ 후속연ꡬ가 진행될 것이라 νŒλ‹¨λœλ‹€. 두 번째 ν•œκ³„λŠ” RCP 4.5 / RCP 8.5 μ‹œλ‚˜λ¦¬μ˜€κ°€ 10λ…„μ˜ λΉˆλ„λ‘œ μˆ˜ν–‰λ˜μ—ˆλ‹€λŠ” 것이닀. μ„Έ 번째 ν•œκ³„μ μ€ μ‚¬νšŒ λ³€ν™” μš”μΈμ΄ λ°˜μ˜λ˜μ§€ μ•Šμ•˜λ‹€λŠ” 것 μž…λ‹ˆλ‹€. λ„€ λ²ˆμ§ΈλŠ” κ²€μ¦μ˜ ν•œκ³„μž…λ‹ˆλ‹€. λ³Έ μ—°κ΅¬μ—μ„œλŠ” μ„œμšΈμ‹œμ˜ 유좜수λ₯Ό κ³„μ‚°ν•˜κΈ° μœ„ν•΄ μ‚°μˆ  방정식과 GIS Arc-hydroλ₯Ό μ‚¬μš©ν•˜μ˜€λ‹€.μΆ”ν›„ SWMM λ“±μ˜ ν™μˆ˜ 해석 ν”„λ‘œκ·Έλž¨μ„ ν™œμš©ν•˜μ—¬ 좔가적인 검증이 λ˜μ–΄μ•Ό ν•œλ‹€. λ”°λΌμ„œ, μœ„μ˜ λ„€ 가지 ν•œκ³„λ₯Ό κ·Ήλ³΅ν•˜κΈ° μœ„ν•΄ 후속 연ꡬ가 μˆ˜ν–‰λ˜μ–΄μ•Ό ν•  κ²ƒμœΌλ‘œ νŒλ‹¨λœλ‹€. 특히 첫 번째 문제점인 κΈ°ν›„λ³€ν™” μ‹œλ‚˜λ¦¬μ˜€μ˜ λΆˆν™•μ‹€μ„± ν•œκ³„μ μ€ ν›„μ†λ˜λŠ” μ„Έ 가지 ν•œκ³„μ μ„ λ°œμƒμ‹œν‚€κΈ°μ—, ν•„μˆ˜μ μœΌλ‘œ ν•΄κ²°λ˜μ–΄μ•Ό ν•œλ‹€.The social and economic damage caused by climate change has increased rapidly over the last several decades, with increasing instances of heat waves, floods, and extreme rainfall. Of these, the damage caused by extreme rainfall is still ongoing, and more extreme rainfall is expected in Korean Peninsula in the future. There was up to 110.5 mm/hr of rainfall in Seoul, which caused 69 casualties and approximately USD 27.6 million in economic damage. Most of the causes of flooding in modern cities include a sharp increase in non-permeable packaging surfaces and a lack of water circulation facilities. According to climate change scenarios provided by the Korea Meteorological Administration, the average rainfall in cities over the next 100 years is expected to decrease. However, it is predicted that future instances of heavy rain will occur in the future, causing large amounts of local damage. If the current state of infrastructure is not equipped with repair or mitigating technologies, the damage will be significant. This study was conducted based on the following three objectives. First, to quantitatively analyze urban flood damage over the next 80 years (2020-2100) that could be caused by the climate change scenario provided by the Korea Meteorological Administration. Second, this study was selected disaster mitigation facilities and analyzed their impact on disaster mitigation. It also arranges and designs facilities based on an evidence-based planning. Sustainable facilities were selected by introducing eco-friendly facilities for future generations as mitigate technologies. Third, through the development of the HCFD (Hazard Capacity Factor Design) model, the capacity and performance of the facilities that may change in the future were analyzed. HCFD model was used to consider ways to maintain mitigating technologies. In order to achieve these goals, a total of three mitigating technologies have been installed. This includes water tanks, permeable pavement, and ecological waterways. In the case of water tanks, the capacity was calculated by referring to the statutes designated by the Ministry of Environment. Also, an Arc-GIS ArcHydro Plug-in was used to calculate the scale of each technology and watershed was analyzed. The precipitation provided by the climate change scenario was analyzed on an hourly basis to determine the extent to which watershed affects it, and the Huff dimensionless curve was used for this purpose. These three mitigating technologies can contribute to flooding by increasing the storage capacity of rainwater. This study suggests that all floods can be reduced by RCP8.5 in 2050, 2060. Although there will be run-off after 2070, it is analyzed that technology will significantly reduce the volume of the flood. It is deemed that a one-year analysis should be conducted in consideration of the maintenance aspects in the future. Furthermore, removal timing of the non-point source pollutant was calculated. In the case of water tanks, the amount of non-point source pollutant accumulated inside and the removal timing were calculated through MOUSE regression analysis. Internal management of water tank is classified into caution stage, general stage and safe stage. There were nine local governments that corresponded to the caution stage, ten local governments of general stage and five local governments of safe stage. There are three main conclusions drawn from the results of this study. First is that the possibility of flooding that could occur according to climate change scenarios was analyzed at a 10-year frequency. Both the RCP 8.5 scenario and RCP 4.5 scenario showed frequent flooding after 2070. For the RCP 8.5 scenario, it is predicted that the year 2090 has the highest amount of precipitation. However, for RCP 4.5 scenario 2100, the maximum daily rainfall is approximately 690 mm, with hourly precipitation of 238 mm. The second is that capacity of each technology was analyzed. According to the installation rules assumed in this study, the volume of water tanks that can be installed throughout the Seoul Metropolitan Government is 776,588 mΒ³, permeable pavement is 89,049 mΒ³, ecological waterway is 81,986 mΒ³. It is siginificant that each local government has suggested an efficient combination of two technologies. Third, the amount of runoff that can be reduced by each mitigating technology was quantified. This study has identified that flooding at the local level will be more frequent and is meaningful in analyzing the quantitative effects of disaster mitigation technologies. Besides, when each local government installed flood mitigation technology in the future, quantification data would be provided to ensure optimized decision making for each situation. The limitations of this study can be diagnosed by dividing them into four parts. The first limitation is uncertainty about climate change scenarios. Since changes in carbon emissions or scenarios can significantly change precipitation values, it is believed that future studies will develop into a more significant study if a scenario with fewer errors is used. The second limitation is that the study was conducted at a frequency of 10 years, as both RCP4.5 / RCP8.5 scenarios were analyzed daily. Third, social change factors are not reflected. Fourth is the limitation of verification. In this study, an arithmetic equation and GIS Arc-hydro were used to calculate the run-off in the Seoul Metropolitan Government. The most ideal method to verification is to compare the results with other software. The reliability of this study can be improved by comparing the amount of runoff before applying technologies using programs such as SWMM, STORM, and MUSIC. Future studies, therefore, should be carried out to overcome the above four limitations. In particular, uncertainty problem of the climate change scenario should be solved.Chapter 1. Introduction 1 1.1 Background 1 1.2 Objectives 5 1.3 Scope 6 1.4 Definition of Floods 8 1.5 Vulnerability 11 Chapter 2. Literature Review 14 2.1 Overview 14 2.2 Policy Review 19 2.3 Types of Defense Technologies 21 2.4 Types of Analysis Programs 33 2.5 Target Site 37 2.6 Climate Change Scenarios 38 Chapter 3. Methodology 41 3.1 Hydrologic Analysis 41 3.2 Application of Mitigation Technology and Estimation of flood damage 46 3.3 Calculation of Current Rainfall Capacity and Run-off 48 3.4 Estimation of Hourly Precipitation in Climate Change Scenarios (RCP 8.5/RCP 4.5) using the Huff curve 51 3.5 The Concept of HCFD (Hazard Capacity Factor Design) Model for observing Future Ability Changes of Facilities 53 Chapter 4. Results 56 4.1 Site Analysis 56 4.2 The 10-year frequency flood damage analysis 65 4.3 Variation of the flooded area after application of disaster mitigating technology 71 4.4 Amount of non-point pollutant deposits in the water tank and maintenance time using the MOUSE regression equation 86 Chapter 5. Summary and Conclusions 94Maste

    Establishment and Application of Spatial Distribution Model of Roof Greening Based on GIS Technology

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    The stage from the beginning of the 21st century to now is the stage of the scale development of roof greening(RG) in China. With the continuous progress of urban construction, on the one hand, the ecological environment is deteriorating, on the other hand, the available green space in the urban center area becomes more and more scarce. The development of this contradiction promotes the rapid development of RG. RG plays an important role in enriching urban landscape, increasing urban green quantity, reducing urban heat island effect, conserving rainwater and reducing temperature, and creating a new green space for the city, including leisure, entertainment and ecology, and improving urban ecological landscape. This paper mainly studies the establishment and application of spatial distribution(SD) model of RG Based on GIS technology. Through understanding the SD design of RG, the paper investigates and analyzes the status quo of green space of roof, macro layout and the integration of multiple functional spaces. This paper studies and establishes a multiobjective optimization model of SD of RG, and analyzes the purification effect of RG on rainwater pollutants and the overall performance of ecosystem service equity. The results show that 26.31% of the people think that the degree of RG is insufficient, and 5.14% think that RG is scarce. In the cognition of the status of RG space, 12.41% of people don't care about RG, 8.69% think it is face engineering, and even 9.31% think it is waste of resources, which indicates that the promotion of RG needs to be improved

    Nature-based solutions efficiency evaluation against natural hazards: modelling methods, advantages and limitations

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    Nature-based solutions (NBS) for hydro-meteorological risks (HMRs) reduction and management are becoming increasingly popular, but challenges such as the lack of well-recognised standard methodologies to evaluate their performance and upscale their implementation remain. We systematically evaluate the current state-of-the art on the models and tools that are utilised for the optimum allocation, design and efficiency evaluation of NBS for five HMRs (flooding, droughts, heatwaves, landslides, and storm surges and coastal erosion). We found that methods to assess the complex issue of NBS efficiency and cost-benefits analysis are still in the development stage and they have only been implemented through the methodologies developed for other purposes such as fluid dynamics models in micro and catchment scale contexts. Of the reviewed numerical models and tools MIKE-SHE, SWMM (for floods), ParFlow-TREES, ACRU, SIMGRO (for droughts), WRF, ENVI-met (for heatwaves), FUNWAVE-TVD, BROOK90 (for landslides), TELEMAC and ADCIRC (for storm surges) are more flexible to evaluate the performance and effectiveness of specific NBS such as wetlands, ponds, trees, parks, grass, green roof/walls, tree roots, vegetations, coral reefs, mangroves, sea grasses, oyster reefs, sea salt marshes, sandy beaches and dunes. We conclude that the models and tools that are capable of assessing the multiple benefits, particularly the performance and cost-effectiveness of NBS for HMR reduction and management are not readily available. Thus, our synthesis of modelling methods can facilitate their selection that can maximise opportunities and refute the current political hesitation of NBS deployment compared with grey solutions for HMR management but also for the provision of a wide range of social and economic co-benefits. However, there is still a need for bespoke modelling tools that can holistically assess the various components of NBS from an HMR reduction and management perspective. Such tools can facilitate impact assessment modelling under different NBS scenarios to build a solid evidence base for upscaling and replicating the implementation of NBS

    Urban Heat Island Effects in Tropical Climate

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    This paper reviews some of the characteristics of urban climates and the causes and effects of urban heat island (UHI) issues in the tropical climate. UHI effect is a kind of heat accumulation phenomenon within the urban areas due to urban construction and human activities. It is recognized as the most evident characteristic of urban climate. The increase of land surface temperature in San Juan, Puerto Rico, caused by the UHI effect was influenced by the change of land use and material types in construction. The impacts of daily temperature, surface albedo, evapotranspiration (ET), and anthropogenic heating on the near-surface climate are discussed. Analyzed data and field measurements indicate that increasing albedo and vegetation cover can be effective in reducing the surface and air temperatures near the ground. Some mitigation and prevention measures are proposed for the effects of UHI, such as a flash flood warning system

    Nature-based solutions efficiency evaluation against natural hazards: Modelling methods, advantages and limitations

    Get PDF
    Nature-based solutions (NBS) for hydro-meteorological risks (HMRs) reduction and management are becoming increasingly popular, but challenges such as the lack of well-recognised standard methodologies to evaluate their performance and upscale their implementation remain. We systematically evaluate the current state-of-the art on the models and tools that are utilised for the optimum allocation, design and efficiency evaluation of NBS for five HMRs (flooding, droughts, heatwaves, landslides, and storm surges and coastal erosion). We found that methods to assess the complex issue of NBS efficiency and cost-benefits analysis are still in the development stage and they have only been implemented through the methodologies developed for other purposes such as fluid dynamics models in micro and catchment scale contexts. Of the reviewed numerical models and tools MIKE-SHE, SWMM (for floods), ParFlow-TREES, ACRU, SIMGRO (for droughts), WRF, ENVI-met (for heatwaves), FUNWAVE-TVD, BROOK90 (for landslides), TELEMAC and ADCIRC (for storm surges) are more flexible to evaluate the performance and effectiveness of specific NBS such as wetlands, ponds, trees, parks, grass, green roof/walls, tree roots, vegetations, coral reefs, mangroves, sea grasses, oyster reefs, sea salt marshes, sandy beaches and dunes. We conclude that the models and tools that are capable of assessing the multiple benefits, particularly the performance and cost-effectiveness of NBS for HMR reduction and management are not readily available. Thus, our synthesis of modelling methods can facilitate their selection that can maximise opportunities and refute the current political hesitation of NBS deployment compared with grey solutions for HMR management but also for the provision of a wide range of social and economic co-benefits. However, there is still a need for bespoke modelling tools that can holistically assess the various components of NBS from an HMR reduction and management perspective. Such tools can facilitate impact assessment modelling under different NBS scenarios to build a solid evidence base for upscaling and replicating the implementation of NBS

    Flood risk management in sponge cities:The role of integrated simulation and 3D visualization

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    The Sponge City concept has been promoted as a major programme of work to address increasing flood risk in urban areas, in combination with wider benefits for water resources and urban renewal. However, realization of the concept requires collaborative engagement with a wide range of professionals and with affected communities. Visualization can play an important role in this process. In this research, a sponge city flood simulation and forecasting system has been built which combines hydrological data, topographic data, GIS data and hydrodynamic models in real-time and interactive display in a three-dimensional environment. Actual and design flood events in a pilot sponge city have been simulated. The validation results show that the simulated urban water accumulation process is consistent with the actual monitoring data. Use of advanced virtual reality technology can enable simulations to be placed in the wider design context including enhanced awareness of multiple functions of urban ecosystems. This procedure can therefore reduce the information communication gap and encourage innovation regarding low impact development required for sponge city construction

    Wadi Flash Floods

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    This open access book brings together research studies, developments, and application-related flash flood topics on wadi systems in arid regions. The major merit of this comprehensive book is its focus on research and technical papers as well as case study applications in different regions worldwide that cover many topics and answer several scientific questions. The book chapters comprehensively and significantly highlight different scientific research disciplines related to wadi flash floods, including climatology, hydrological models, new monitoring techniques, remote sensing techniques, field investigations, international collaboration projects, risk assessment and mitigation, sedimentation and sediment transport, and groundwater quality and quantity assessment and management. In this book, the contributing authors (engineers, researchers, and professionals) introduce their recent scientific findings to develop suitable, applicable, and innovative tools for forecasting, mitigation, and water management as well as society development under seven main research themes as follows: Part 1. Wadi Flash Flood Challenges and Strategies Part 2. Hydrometeorology and Climate Changes Part 3. Rainfall–Runoff Modeling and Approaches Part 4. Disaster Risk Reduction and Mitigation Part 5. Reservoir Sedimentation and Sediment Yield Part 6. Groundwater Management Part 7. Application and Case Studies The book includes selected high-quality papers from five series of the International Symposium on Flash Floods in Wadi Systems (ISFF) that were held in 2015, 2016, 2017, 2018, and 2020 in Japan, Egypt, Oman, Morocco, and Japan, respectively. These collections of chapters could provide valuable guidance and scientific content not only for academics, researchers, and students but also for decision-makers in the MENA region and worldwide

    A FRAMEWORK FOR SUSTAINABLE RESILIENT HOUSES ON THE COASTAL AREAS OF KHANH HOA, VIETNAM

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    Vietnam is a developing country and a storm-prone country in Asia. The impacts of tropical storms on Vietnamβ€Ÿs residences are the main focus of study in this research. The lack of knowledge and storm-proofing techniques for improving resilient houses are unresolved issues in this place. The consequences of this limitation were demonstrated through 55% of collapsed houses and 10% of flooded areas in Nha Trang city after the storm 2017. This research was based on the community's needs to develop a set of guidance for improving stability of domestic buildings in storm-prone areas. The aim of the research is to produce a framework for designing sustainable resilient houses in Vietnamβ€Ÿs coastal areas. That framework will solve a part of building problems from hurricane impacts with the resilient designs in terms of floodproofing and wind mitigation. This research also promotes the application and development of sustainable dwellings in Vietnam. Sustainable development in residences will increase building performance in two areas: energy and resource efficiency. The quantitative and qualitative data in the study were collected by the use of mixed-method approaches. Those approaches included observation, questionnaire, interview, and simulation. The observation gathered evidence of storm impacts on Nha Trang city in recent years. The community's needs were obtained with 50 responses to the questionnaire. To understand the depth of local problems, interviews with 5 local professionals and 3 householders were conducted. The main findings involved the solutions, techniques, benefits, and challenges of sustainable resilience in coastal residences. Besides, the weaknesses of existing buildings were defined through the wind simulation of Design-Builder and Autodesk CFD. The framework has three main stages for designing sustainable resilient houses in Vietnam's coastal areas. Those stages are data collection, design specifications, and product design. In particular, the framework was validated by a prototype design. The simulation results were evidence to define building performance in terms of storm resilience and sustainability. Hence, the framework and the prototype confirmed the effects of the research on society and people's awareness
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